{"updated":"2025-01-20T02:07:18.520373+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00187708","sets":["6504:9465:9471"]},"path":["9471"],"owner":"6748","recid":"187708","title":["小規模構成で実施可能な大量ツイート分析手法の提案(2) − 「けものフレンズ」ツイートを対象とした分析方法検証"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-03-13"},"_buckets":{"deposit":"4fa9141d-82fa-4de4-88ce-d0ee7039acf0"},"_deposit":{"id":"187708","pid":{"type":"depid","value":"187708","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"小規模構成で実施可能な大量ツイート分析手法の提案(2) − 「けものフレンズ」ツイートを対象とした分析方法検証","author_link":["425211","425213","425212"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"小規模構成で実施可能な大量ツイート分析手法の提案(2) − 「けものフレンズ」ツイートを対象とした分析方法検証"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データとウェブ","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2018-03-13","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"USP研"},{"subitem_text_value":"USP研"},{"subitem_text_value":"金沢大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/187708/files/IPSJ-Z80-4B-03.pdf","label":"IPSJ-Z80-4B-03.pdf"},"date":[{"dateType":"Available","dateValue":"2018-04-25"}],"format":"application/pdf","filename":"IPSJ-Z80-4B-03.pdf","filesize":[{"value":"502.6 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"e0444a17-d6e2-4492-8e7b-9d463c54c74d","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松浦, 智之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"當仲, 寛哲"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大野, 浩之"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ツイッター分析は、ニュース番組でも頻繁に用いられるなど、その需要は増加している。しかしその手法を調査しても、大企業等が大きな予算や設備を導入して行う事例が殆どであり、個人の例は殆ど報告されていない。本研究では個人等がコンピュータ1台で行える手法を研究した。第2報では2017年流行語大賞にもノミネートされた「けものフレンズ」に関連するツイートの分析方法を例示する。いずれの例にも、データベースミドルウェアは用いず、UNIXコマンド及び、結果表示のために無料で利用できる表計算ソフトのみを用いた。収集データがファイルやディデレクトリに的確に配置されていれば、専門的な分析ソフトなしでもある程度分析できることを示す。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"362","bibliographic_titles":[{"bibliographic_title":"第80回全国大会講演論文集"}],"bibliographicPageStart":"361","bibliographicIssueDates":{"bibliographicIssueDate":"2018-03-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2018"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"created":"2025-01-19T00:54:21.761469+00:00","id":187708,"links":{}}